scholarly journals Specifics of logit and probit regression in education sciences - why wouldn't we use it?

2020 ◽  
Vol 15 (6) ◽  
pp. 1557-1568
Author(s):  
Sinisa Opic
Keyword(s):  
Social Sciences ◽  
Linear Regression ◽  
Comparative Research ◽  
Regression Models ◽  
Linear Regression Models ◽  
Probit Regression ◽  
Regression Methods ◽  
Logit Regression ◽  
The Social ◽  
Keywords Education

Regression is one of the dominant analysis methods used in the social sciences and educational sciences. There are different regression methods based on the type of research that is being conducted. The probit and logit regression models are regression methods which are being used recently by most researchers. However, their interpretations are not straightfoward and most researchers end up misinterepreting the results from the probit and logit regression models. This research therefore aims to examine the differences between the probit and logit models, in comparison with other linear regression models. Using a comparative research design, this study utilises resources from previous researchers, hence, the study took a form of a literature review. The results of this study is essential to educational and social sciences researchers who make use of the probit, logit and other regression methods. The research also explains why logit and probit should be used in place of other regression models.   Keywords: education sciences; Linear regression; Logit; Probit; Regression

The social meaning of a merger: The evaluation of an Andalusian Spanish consonant merger (ceceo)

2021 ◽  
pp. 1-30
Author(s):  
Brendan Regan
Keyword(s):  
Linear Regression ◽  
Social Status ◽  
Regression Models ◽  
Language Attitudes ◽  
Spontaneous Speech ◽  
Mixed Effects ◽  
Social Meaning ◽  
Linear Regression Models ◽  
Social Evaluation ◽  
The Social

Abstract This study analyzes the social evaluations of the Andalusian Spanish ceceo merger and its split, distinción. A matched-guise experiment was created by digitally manipulating spontaneous speech from twelve Western Andalusian speakers, varying only in syllable-initial [s̪] and [θ] for <s> and <z,ci,ce>, creating ceceo and distinción guises. Based on 221 listeners from Huelva and Lepe, Spain, mixed effects linear regression models found that speakers with distinción guises were evaluated as being of higher social status, more urban, and more formal than speakers with ceceo guises. Additionally, listeners' comments referred not only to the sounds and graphemes, but also to the merger itself and its social connotations. The implications are two-fold: (i) consonant mergers may be subject to more overt social evaluation than vocalic mergers; and (ii) a merger can acquire social meaning, and this meaning in turn, may promote its split. (Mergers, splits, sociolinguistic perception, language attitudes, Andalusian Spanish, sociophonetics, dialect levelling, ceceo, distinción)*

Interpreting Regression Diagnostics

2004 ◽  
Vol 29 (3) ◽  
pp. 369-373
Author(s):  
KX Karakostas
Keyword(s):  
Social Sciences ◽  
Linear Regression ◽  
Regression Models ◽  
Regression Diagnostics ◽  
Linear Regression Models

This article presents a technique that will help teachers, researchers, and other people who use the linear regression models, especially those in education and social sciences, to understand and interpret the residuals graphics better.

scholarly journals ANALISIS PENGARUH LUAS PANEN DAN PRODUKTIVITAS UBI KAYU DI KABUPATEN KEBUMEN DENGAN MENGGUNAKAN REGRESI LINIER BERGANDA

2021 ◽  
Vol 13 (2) ◽  
pp. 127
Author(s):  
Umi Muslimah ◽  
Agus Sugandha
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Staple Food ◽  
Linear Regression Models ◽  
Regression Methods ◽  
Staple Foods ◽  
Existing Data

Cassava  are one of the staple foods in place of rice. However, today almost no one consumes cassava  as a staple food substitute for rice. Indonesia is ranked third as the world's largest producer of cassava. Therefore, to maintain the value of yam production, the author will look for linear regression models as well as the best models with factors that are harvest area and productivity. Productivity is defined as the result of a comparison between the area of harvest and production. To search for regression models use multiple linear regression methods, while the best models use stepwise methods. Based on existing data, the best model is obtained with negative interception and influenced by productivity and the extent of the yam harvest.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

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